The use of stabilized weights is often recommended to gain precision and efficiency [1]}, [2]}, particularly when the weights are highly variable. In the implementations of MAIC in this article, the fitted weighted outcome model is considered to be “saturated” (i.e., cannot be misspecified) because it is a marginal model of outcome on a time-fixed binary treatment [3]}. For saturated models, stabilized and unstabilized weights give identical results [3]}. Nevertheless, weight stabilization is encouraged when the weighted outcome model is unsaturated, e.g. with dynamic (time-varying) or continuous-valued treatment regimens [5]}, [6]}.
